我是一个学生，我真的被这个问题困扰了两个星期，在互联网上没有多少问题。我真的需要帮助：
我遵循了本教程：https://docs.microsoft.com/fr-fr/azure/hdinsight/spark/apache-spark-machine-learning-mllib-ipython
当我从RDD中检索一行以观察inspections.take(1)或df.show(5)之类的数据模式时，我遇到了这个错误
> Py4JJavaError Traceback (most recent call
> last) <ipython-input-13-eb589bae8d4b> in <module>()
> ----> 1 df.show(5)
>
> ~/anaconda3/lib/python3.6/site-packages/pyspark/sql/dataframe.py in
> show(self, n, truncate, vertical)
> 376 """
> 377 if isinstance(truncate, bool) and truncate:
> --> 378 print(self._jdf.showString(n, 20, vertical))
> 379 else:
> 380 print(self._jdf.showString(n, int(truncate), vertical))
>
> ~/anaconda3/lib/python3.6/site-packages/py4j/java_gateway.py in
> __call__(self, *args) 1255 answer = self.gateway_client.send_command(command) 1256 return_value
> = get_return_value(
> -> 1257 answer, self.gateway_client, self.target_id, self.name) 1258 1259 for temp_arg in temp_args:
>
> ~/anaconda3/lib/python3.6/site-packages/pyspark/sql/utils.py in
> deco(*a, **kw)
> 61 def deco(*a, **kw):
> 62 try:
> ---> 63 return f(*a, **kw)
> 64 except py4j.protocol.Py4JJavaError as e:
> 65 s = e.java_exception.toString()
>
> ~/anaconda3/lib/python3.6/site-packages/py4j/protocol.py in
> get_return_value(answer, gateway_client, target_id, name)
> 326 raise Py4JJavaError(
> 327 "An error occurred while calling {0}{1}{2}.\n".
> --> 328 format(target_id, ".", name), value)
> 329 else:
> 330 raise Py4JError(
>
> Py4JJavaError: An error occurred while calling o37.showString. :
> org.apache.spark.SparkException: Job aborted due to stage failure:
> Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0
> in stage 0.0 (TID 0, localhost, executor driver):
> org.apache.spark.api.python.PythonException: Traceback (most recent
> call last): File
> "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py",
> line 372, in main
> process() File "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py",
> line 367, in process
> serializer.dump_stream(func(split_index, iterator), outfile) File
> "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py",
> line 390, in dump_stream
> vs = list(itertools.islice(iterator, batch)) File "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/util.py",
> line 100, in wrapper
> return f(*args, **kwargs) File "<ipython-input-10-9aa45565a8c1>", line 3, in csvParse
> ModuleNotFoundError: No module named 'StringIO'
>
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571)
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) at
> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at
> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at
> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source) at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:619)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at
> org.apache.spark.scheduler.Task.run(Task.scala:121) at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
>
> Driver stacktrace: at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
> at scala.Option.foreach(Option.scala:257) at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2082) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2101) at
> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:365)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3384)
> at
> org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2545)
> at
> org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2545)
> at org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3365)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3364) at
> org.apache.spark.sql.Dataset.head(Dataset.scala:2545) at
> org.apache.spark.sql.Dataset.take(Dataset.scala:2759) at
> org.apache.spark.sql.Dataset.getRows(Dataset.scala:255) at
> org.apache.spark.sql.Dataset.showString(Dataset.scala:292) at
> sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:483) at
> py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at
> py4j.Gateway.invoke(Gateway.java:282) at
> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at py4j.commands.CallCommand.execute(CallCommand.java:79) at
> py4j.GatewayConnection.run(GatewayConnection.java:238) at
> java.lang.Thread.run(Thread.java:745) Caused by:
> org.apache.spark.api.python.PythonException: Traceback (most recent
> call last): File
> "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py",
> line 372, in main
> process() File "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py",
> line 367, in process
> serializer.dump_stream(func(split_index, iterator), outfile) File
> "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/serializers.py",
> line 390, in dump_stream
> vs = list(itertools.islice(iterator, batch)) File "/Users/sabbar/anaconda3/lib/python3.6/site-packages/pyspark/python/lib/pyspark.zip/pyspark/util.py",
> line 100, in wrapper
> return f(*args, **kwargs) File "<ipython-input-10-9aa45565a8c1>", line 3, in csvParse
> ModuleNotFoundError: No module named 'StringIO'
>
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571)
> at
> org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406)
> at
> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) at
> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at
> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at
> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409) at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source) at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:619)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:255)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:836)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at
> org.apache.spark.scheduler.Task.run(Task.scala:121) at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> ... 1 more
这是代码：
from pyspark.ml import Pipeline
from pyspark.ml.classification import LogisticRegression
from pyspark.ml.feature import HashingTF, Tokenizer
from pyspark.sql import Row
from pyspark.sql.functions import UserDefinedFunction
from pyspark.sql.types import *
import pyspark
#from pyspark import SparkContext
#sc = SparkContext("local", "Simple App")
from pyspark.context import SparkContext
from pyspark.sql.session import SparkSession
from py4j.protocol import Py4JJavaError
def csvParse(s):
import csv
from StringIO import StringIO
sio = StringIO(s)
value = csv.reader(sio).next()
sio.close()
return value
inspections = sc.textFile('Chicago_Street_Names.csv').map(csvParse)
inspections.take(1)
请帮助我，这是下周要完成的项目
答案 0 :(得分：0)
正如@pault在注释中建议的那样，您无需编写自己的函数即可解析简单的csv文件。您可以使用sc.read.csv(FILEPATH)。
如果您想按原样继续操作，则可以替换
from StringIO import StringIO与from io import StringIO。
在新的Python 3版本中，StringIO package已被io package取代。
答案 1 :(得分：0)
我在运行 3.1 Spark 版本时遇到了同样的问题，我只是在 Anaconda 上使用 Spark 2.4.0 和 Python 3.7 创建了一个新环境。